Real-World Evidence: Methods and Mastery

About this Book

The Advanced Methodology Reference for Senior RWE Practitioners

Real-World Evidence: Methods and Mastery is the most technically advanced volume in the Evidence Mastery series — and one of the most comprehensive treatments of advanced RWE methodology available in the scientific literature. Written for methodologists, regulators, senior researchers, and advanced practitioners who need to go well beyond the basics, it covers the full architecture of modern causal inference and real-world evidence generation.

The book is structured in six parts. Part I establishes the foundations: the RWE ecosystem as a system of systems, advanced data quality and validation, large-scale data linkage, and measurement error and misclassification. Part II is the methodological core — covering target trial emulation, advanced propensity score methods, instrumental variables, marginal structural models, G-methods and causal diagrams, and sensitivity analyses with quantitative bias analysis.

Part III explores advanced analytics including longitudinal data methods, survival analysis, high-dimensional propensity scores, machine learning for causal inference, and synthetic data and digital twins. Part IV covers the full landscape of real-world trials — pragmatic trials, registry-based RCTs, decentralised trials, and adaptive designs. Part V is a comprehensive treatment of global regulatory science (FDA, EMA/DARWIN EU, MHRA, PMDA, Health Canada, and ICH M14). Part VI closes with applications across drug development, medical devices, vaccines, and the emerging field of longevity and geroscience.

Who This Book Is For

Senior methodologists

Regulatory scientists

Senior researchers

HTA assessors

Epidemiologists

Biostatisticians

Data scientists

Academic researchers

Contents

Six Parts — 27 Chapters of Advanced Methodology

Part I · 60–80 pages

Foundations of Advanced RWE

The Architecture of Real-World Evidence — RWE stack, maturity models, infrastructure
Advanced Data Quality and Validation — temporal consistency, algorithm validation, regulatory expectations
Data Linkage at Scale — PPRL, Bloom filters, secure multi-party computation
Measurement Error and Misclassification — correction methods, SIMEX, Bayesian correction

Part II · 120–150 pages

Study Design and Causal Inference

Target Trial Emulation — time-zero alignment, grace periods, pitfalls, case studies
Propensity Score Methods (Advanced) — high-dim PS, optimal matching, IPTW, overlap weights
Instrumental Variables — physician preference, geographic variation, 2SLS, G-estimation
Marginal Structural Models — time-varying confounding, IPC weighting, pooled logistic
G-Methods and Causal Diagrams — DAGs, colliders, G-computation, transportability
Sensitivity Analyses and Quantitative Bias Analysis — E-values, Monte Carlo bias modelling

Part III · 80–100 pages

Advanced Analytics

Longitudinal Data Methods — repeated measures, mixed-effects models, time-varying covariates
Survival and Time-to-Event Models — competing risks, multi-state models, recurrent events
High-Dimensional Propensity Scores — variable selection, penalised regression
Machine Learning for Causal Inference — causal forests, meta-learners, double ML
Synthetic Data and Digital Twins — generation, privacy models, regulatory considerations

Part IV · 60–80 pages

Real-World Trials

Pragmatic Clinical Trials — PRECIS-2, embedded trials, regulatory acceptance
Registry-Based Randomised Trials — infrastructure, randomisation within registries
Decentralised and Hybrid Trials — remote recruitment, wearables, digital endpoints
Adaptive Designs — Bayesian adaptive, platform trials, operational challenges

Part V · 60–80 pages

Regulatory Science

FDA RWE Framework — data considerations, use cases, case studies
EMA and DARWIN EU — architecture, data partners, future directions
MHRA, PMDA, Health Canada — national frameworks and cross-agency comparisons
ICH M14 and Global Harmonization — harmonised definitions and methodological expectations

Part VI · 40–60 pages

Applications Across the Life Sciences

Drug Development — external control arms, label expansion, post-marketing commitments
Medical Devices and Diagnostics — post-market surveillance, digital health technologies
Vaccines and Public Health — effectiveness studies, safety monitoring, outbreak analytics
Longevity and Geroscience — aging biomarkers, multimorbidity, geroscience trials

Real-World Evidence:Methods and Mastery

The Advanced Methodology Reference for Senior RWE Practitioners

Six Parts — 27 Chapters of Advanced Methodology

Other Books in the Series

Real-World Evidence:
Methods and Mastery